2: Diversity. 2. Diversity. Some Concepts of Wireless Communication
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1 2. Diversity 1
2 Main story Communication over a flat fading channel has poor performance due to significant probability that channel is in a deep fade. Reliability is increased by providing more resolvable signal paths that fade independently. Diversity can be provided across time, frequency and space. Name of the game is how to exploit the added diversity in an efficient manner. 2
3 Baseline: AWGN Channel BPSK modulation Error probability decays exponentially with SNR. 3
4 Gaussian Detection 4
5 Rayleigh Flat Fading Channel BPSK: Coherent detection. Conditional on h, Averaged over h, at high SNR. 5
6 Rayleigh vs AWGN 6
7 Conditional on h, Typical Error Event When error probability is very small. When error probability is large: Typical error event is due to channel being in deep fade rather than noise being large. 7
8 BPSK, QPSK and 4-PAM BPSK uses only the I-phase.The Q-phase is wasted. QPSK delivers 2 bits per complex symbol. To deliver the same 2 bits, 4-PAM requires 4 db more transmit power. QPSK exploits the available degrees of freedom in the channel better. A good communication scheme exploits all the available d.o.f. in the channel. 8
9 Time Diversity Time diversity can be obtained by interleaving and coding over symbols across different coherent time periods. Coding alone is not sufficient! 9
10 Example:GSM Amount of time diversity limited by delay constraint and how fast channel varies. In GSM, delay constraint is 40 ms (voice). To get full diversity of 8, needs v > 30 km/h at f c = 900 MHz. Not Notenough enoughat atlow lowspeed, then thenfh FH between between khz khzchannels. 10
11 Simplest Code: Repetition After interleaving over L coherence time periods, Repetition coding: for all where and This is classic vector detection in white Gaussian noise. 11
12 Geometry For BPSK Is a sufficient statistic (matched filtering). Reduces to scalar detection problem: 12
13 Deep Fades Become Rarer 13
14 Performance 14
15 Beyond Repetition Coding Repetition coding gets full diversity, but sends only one symbol every L symbol times. Does not exploit fully the degrees of freedom in the channel. (analogy: PAM vs QAM) How to do better? Block Blockand andconvolutional convolutionalcoding codingin in addition additiontotointerleaving interleavingallow allowtime diversity diversity (diversity (diversitygain gain = minimum minimumhamming Hammingdistance). Performance Performancedepends dependson onchannel statistics statistics (Raleigh). (Raleigh). There Thereare are specific specificcoding coding (based (basedon onit) IT) to todefine a UNIVERSAL UNIVERSAL CODE CODE (independent (independentof ofchannle channlestatistics). 15
16 Example: Rotation code (L=2) x 1, x 2 are two BPSK symbols before rotation. where d 1 and d 2 are the distances between the codewords in the two directions. 16
17 Rotation vs Repetition Coding Rotation code uses the degrees of freedom better! 17
18 Product Distance product distance Choose the rotation angle to maximize the worst-case product distance to all the other codewords: 18
19 Antenna Diversity Receive Transmit Both Diversity Diversitydepends dependson onantenna antennadistances. Distances Distancesdepends dependson onlocal scattering scattering (for (formobile, high: high: ½ lambda; lambda; for forbase station, station, low: 19 low: several severallambda) lambda) and andcarrier carrierfrequency.
20 Receive Diversity Same as repetition coding in time diversity, except that there is a further power gain. Optimal reception is via matched filtering (receive beamforming). 20
21 Transmit Diversity If transmitter knows the channel, send: maximizes the received SNR by in-phase addition of signals at the receiver (transmit beamforming). Reduce to scalar channel: same as receive beamforming. What happens if transmitter does not know the channel? 21
22 Space-time Codes Transmitting the same symbol simultaneously at the antennas doesn t work. Using the antennas one at a time and sending the same symbol over the different antennas is like repetition coding (bad use of d.o.f). More generally, can use any time-diversity code by turning on one antenna at a time. Space-time codes are designed specifically for the transmit diversity scenario. 22
23 Over two symbol times: Alamouti Scheme Projecting onto the two columns of the H matrix yields: double the symbol rate of repetition coding. 3dB loss of received SNR compared to transmit beamforming. 23
24 Space-time Code Design A space-time code is a set of matrices Full diversity is achieved if all pair-wise differences have full rank. Coding gain determined by the determinants of Time-diversity codes have diagonal matrices and the determinant reduces to squared product distances. 24
25 Frequency Diversity Resolution of multipaths provides diversity. Full diversity is achieved by sending one symbol every L symbol times. But this is inefficient (like repetition coding). Sending symbols more frequently may result in intersymbol interference. Challenge is how to mitigate the ISI while extracting the inherent diversity in the frequency-selective channel. 25
26 Approaches Time-domain equalization (eg. GSM) Direct-sequence spread spectrum (eg. IS-95 CDMA) Orthogonal frequency-division multiplexing OFDM (eg a, Flash-OFDM) 26
27 ISI Equalization Suppose a sequence of uncoded symbols are transmitted. Maximum likelihood sequence detection is performed using the Viterbi algorithm. Can full diversity be achieved? 27
28 Reduction to Transmit Diversity x [1] h 0 y[1] x [2] x [1] h 0 h 1 y[2] Increasing time x [3] x [2] h 0 h 1 h 2 y[3] x [1] x [4] x [3] x [2] h 0 h 1 h 2 y[4] 28
29 MLSD Achieves Full Diversity Space-time code matrix for input sequence Difference matrix for two sequences first differing at is full rank. 29
30 Direct Sequence Spread Spectrum Information sequence Channel encoder Modulator Channel Demodulator Channel decoder Output data Pseudorandom pattern generator Pseudorandom pattern generator Information symbol rate is much lower than chip rate (large processing gain). Signal-to-noise ratio per chip is low. ISI is not significant compared to interference from other users and matched filtering (Rake) is near-optimal. 30
31 Frequency Diversity via Rake Considered a simplified situation (uncoded). Each information bit is spread into two pseudorandom sequences x A and x B (x B = -x A ). X A w[m] X B h h + Decision X B X A h Estimate h Each tap of the match filter is a finger of the Rake. 31
32 ISI vs Frequency Diversity In narrowband systems, ISI is mitigated using a complex receiver. In asynchronous CDMA uplink, ISI is there but small compared to interference from other users. But ISI is not intrinsic to achieve frequency diversity. The transmitter needs to do some work too! 32
33 OFDM: Basic Concept Most wireless channels are underspread (delay spread << coherence time). Can be approximated by a linear time invariant channel over a long time scale. Complex sinusoids are the only eigenfunctions of linear time-invariant channels. Should signal in the frequency domain and then transform to the time domain. 33
34 OFDM 34
35 OFDM OFDM transforms the communication problem into the frequency domain: a bunch of non-interfering sub-channels, one for each sub-carrier. Can apply time-diversity techniques. 35
36 OFDM overhead Cyclic Prefix Overhead = length of cyclic prefix / OFDM symbol time Cyclic prefix dictated by delay spread. OFDM symbol time limited by channel coherence time. Equivalently, the inter-carrier spacing should be much larger than the Doppler spread. Since most channels are underspread, the overhead can be made small. 36
37 Example: Flash OFDM (Flarion) Bandwidth = 1.25 MHz OFDM symbol = 128 samples = 100 μ s Cyclic prefix = 16 samples = 11 μ s delay spread 11 % overhead. 37
38 Channel Uncertainty In fast varying channels, tap gain measurement errors may have an impact on diversity combining performance. The impact is particularly significant in channel with many taps each containing a small fraction of the total received energy. (eg. Ultra-wideband channels) The impact depends on the modulation scheme. 38
39 Summary Fading makes wireless channels unreliable. Diversity increases reliability and makes the channel more consistent. Smart codes yields a coding gain in addition to the diversity gain. This viewpoint of the adversity of fading will be challenged and enriched in later parts of the course. 39
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